We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us
GLOBETECH PUBLISHING LLC

Download Mobile App




Machine Learning Combined with PET/CT Can Predict Heart Attack Risk

By MedImaging International staff writers
Posted on 14 Jan 2022
Print article
Illustration
Illustration

By combining information from two advanced imaging techniques with clinical data, physicians can improve their prediction of heart attacks, according to new research.

When assessed together in an artificial intelligence model, coronary 18F-NaF uptake on PET and quantitative coronary plaque characteristics on CT angiography were found by researchers at the Cedars-Sinai Medical Center (Los Angeles, CA, USA) to be complementary, strong predictors of heart attack risk in patients with established coronary artery disease, providing risk prediction superior to that of clinical data alone.

In everyday clinical practice, predicting a heart attack is challenging. The predicted likelihood of a heart attack typically is based on cardiovascular risk factors and scores, especially in patients with suspected coronary artery disease. However, in patients with confirmed coronary artery disease, cardiovascular risk factors and scores don’t always show the full picture.

In the new study, nearly 300 patients with established coronary atherosclerosis underwent a baseline clinical assessment with evaluation of their cardiovascular risk factor profile. All patients received hybrid coronary 18F-NaF PET and contrast CT coronary angiography. Machine learning - a type of artificial intelligence - was used to calculate a joint score for heart attack risk by incorporating key variables from the clinical assessment, 18F-NaF PET findings and quantitative CT variables.

The machine learning model showed substantial improvement in prediction of heart attack over clinical data alone. This approach demonstrated that 18F-NaF PET and CT angiography are complementary and additive, with the combination of both providing the most robust outcome prediction.

“Recently, advanced imaging techniques have demonstrated considerable promise in determining which coronary artery disease patients are most at risk for a heart attack. These techniques include 18F-sodium fluoride (18F-NaF) PET, which assesses disease activity in the coronary arteries, and CT angiography, which provides a quantitative plaque analysis,” said Piotr J. Slomka, PhD, FACC, FASNC, FCCPM, director of Innovation in Imaging at Cedars-Sinai Medical Center in Los Angeles, California. “Our goal in the study was to investigate whether the information provided by 18F-NaF PET and CT angiography is complementary and could improve prediction of heart attacks with the use of artificial intelligence techniques.”

“18F-NaF PET combined with anatomical imaging provided by CT angiography has the potential to enable precision medicine by guiding the use of advanced therapeutic interventions,” noted Slomka. “Our study supports the use of artificial intelligence methods for integrating multimodality imaging and clinical data for robust prediction of heart attacks.”

Related Links:
Cedars-Sinai Medical Center 


Print article
Radcal

Channels

Radiography

view channel
Image: Physicians using the Zenition 90 Motorized mobile X-ray system (Photo courtesy of Royal Philips)

High-Powered Motorized Mobile C-Arm Delivers State-Of-The-Art Images for Challenging Procedures

During complex surgical procedures, clinicians depend on surgical imaging systems as they navigate challenging anatomy to quickly visualize small anatomical details while minimizing X-ray exposure.... Read more

Ultrasound

view channel
Image: The device creates microbubbles that temporarily disrupt the BBB, permitting the entry of immunotherapy into the brain (Photo courtesy of Northwestern)

Ultrasound Technology Breaks Blood-Brain Barrier for Glioblastoma Treatment

Despite extensive molecular studies, the outlook for patients diagnosed with the aggressive brain cancer known as glioblastoma (GBM) continues to be poor. This is partly due to the blood-brain barrier... Read more

Nuclear Medicine

view channel
Image: 68Ga-NC-BCH whole-body PET imaging rapidly targets an important gastrointestinal cancer biomarker in lesions in GI cancer patients (Photo courtesy of Qi, Guo, et al.; doi.org/10.2967/jnumed.123.267110)

New PET Radiotracer Enables Same-Day Imaging of Key Gastrointestinal Cancer Biomarker

Gastrointestinal cancers rank among the most prevalent cancers worldwide, contributing to over a quarter of all cancer cases and over one-third of cancer-related deaths annually. The initial symptoms of... Read more

Imaging IT

view channel
Image: The new Medical Imaging Suite makes healthcare imaging data more accessible, interoperable and useful (Photo courtesy of Google Cloud)

New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible

Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.